search for: entrezgen

Displaying 4 results from an estimated 4 matches for "entrezgen".

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2007 Jan 26
0
[BioC] problem with biomaRt getHomolog function
...) 1-(317)-536-2730 FAX -----Original Message----- From: Steffen Durinck [mailto:durincks at mail.nih.gov] Sent: Friday, January 26, 2007 9:24 AM To: Kimpel, Mark William Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] problem with biomaRt getHomolog function Hi Mark, I think the rat entrezgene id 613226 is a recently added entrezgene id and is not yet available in Ensembl. Ensembl updates every two months and the last update of entrezgene id 613226 appears to be December 26 of 2006. So this might be the reason. Also I would suggest you use the developmental version of biomaRt (bio...
2013 May 07
1
Problem with biomaRt::getSequence.
Hi, I can run the code some days ago . But cant run now.  Problem 1: Output is ok ensembl = useDataset("hsapiens_gene_ensembl",mart=ensembl) utr5 = getSequence(chromosome=3, start=185514033, end=185535839, type="entrezgene",seqType="5utr", mart=ensembl)  Output :                                                                                                5utr  entrezgene                                                                              Sequence unavailable      10644                      ...
2010 Nov 25
0
[libsvm] predict function error
...uot;,"VEH","VEH","VEH","LPS","LPS","LPS","LPS","LPS")) > tf=t(f) > colnames(tf)=tf[1,] > tf=tf[-1,] > tf=as.data.frame(tf) > array <- apply(tf[,2:24928],c(1,2),as.numeric) > label <- as.factor(tf$ENTREZGENE) > > n <- nrow(array) #get sample number > permutation <- sample(1:n) > array.perm <- array[permutation,] # random permutation of samples > label.perm <- label[permutation] # same permutation of labels > > k <- 5 #set cross validation steps > > for (i in 1...
2013 Oct 27
2
Heteroscedasticity and mgcv.
I have a two part question one about statistical theory and the other about implementations in R. Thank you for all help in advance. (1) Am I correct in understanding that Heteroscedasticity is a problem for Generalized Additive Models as it is for standard linear models? I am asking particularly about the GAMs as implemented in the mgcv package. Based upon my online search it seems that some